Phoneme Recognition Based on Principal Component Analysis

被引：0
|
作者：
Liu, Xianju [1 ]
Mastorakis, Nikos E. [2 ]
Li, Zhongxiao [3 ]
Zhuang, Xiaodong [3 ]
机构：
[1] Univ Elect Sci & Technol China, Sch Informat & Commun Engn, Chengdu, Peoples R China
[2] Tech Univ Sofia, English Language Fac Engn ELFE, Kliment Ohridski 8, Sofia 1000, Bulgaria
[3] Qingdao Univ, Elect & Informat Coll, Qingdao 266071, Peoples R China
来源：
2ND INTERNATIONAL CONFERENCE ON MATHEMATICS AND COMPUTERS IN SCIENCE AND ENGINEERING (MACISE 2020) | 2020年
基金：
美国国家科学基金会;
关键词：
Principal component analysis; phoneme recognition; subspace; representation error;
D O I：
10.1109/MACISE49704.2020.00038
中图分类号：
C93 [管理学]; O22 [运筹学];
学科分类号：
070105 ; 12 ; 1201 ; 1202 ; 120202 ;
摘要：
A new method for vowel phoneme signal recognition is proposed based on principal component analysis. First, the subspace of each vowel signal is estimated by principal component analysis on sevaral vowel signals. Further, the vowel signal to be recognized is divided into frames, and each frames is separately projected into each of the obtained subspaces. In theory, the representation error obtained by projecting the signal into its corresponding subspace is smallest, based on which the vowel phoneme signals can be accurately recognized, The effectiveness of the proposed phoneme recognition method on PCA is proved by experiments.
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页码：175 / 177
页数：3
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